Emologus: a compositional model of emotion detection based on the propositional content of spoken utterances

  • Authors:
  • Marc Le Tallec;Jeanne Villaneau;Jean-Yves Antoine;Agata Savary;Arielle Syssau

  • Affiliations:
  • LI, Université de Tours, France;VALORIA, Université de Bretagne Sud, France;LI, Université de Tours, France;LI, Université de Tours, France and Institute of Computer Science, Polish Academy of Sciences, Warsaw, Poland;Université de Montpellier 3, France

  • Venue:
  • TSD'10 Proceedings of the 13th international conference on Text, speech and dialogue
  • Year:
  • 2010

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Abstract

The ANR EmotiRob project aims at detecting emotions in an original application context: realizing an emotional companion robot for weakened children. This paper presents a system which aims at characterizing emotions by only considering the linguistic content of utterances. It is based on the assumption of compositionality: simple lexical words have an intrinsic emotional value, while verbal and adjectival predicates act as a function on the emotional values of their arguments. The paper describes the semantic component of the system, the algorithm of compositional computation of the emotion value and the lexical emotional norm used by this algorithm. A quantitative and qualitative analysis of the differences between system outputs and expert annotations is given, which shows satisfactory results, with the right detection of emotional valency in 90% of the test utterances.